from torch.cuda.amp import autocast, GradScaler scaler = GradScaler() with autocast(dtype=torch.float16): # or torch.bfloat16 for Hopper+ output = model(input) loss = criterion(output, target) scaler.scale(loss).backward() scaler.step(optimizer) scaler.update()
Warning: Nightly builds are on the bleeding edge and may contain bugs.
conda install pytorch torchvision torchaudio pytorch-cuda=12.6 -c pytorch -c nvidia Use code with caution. Compatibility between CUDA 12.6 and PyTorch
For LLM developers, is a critical component.
from torch.cuda.amp import autocast, GradScaler scaler = GradScaler() with autocast(dtype=torch.float16): # or torch.bfloat16 for Hopper+ output = model(input) loss = criterion(output, target) scaler.scale(loss).backward() scaler.step(optimizer) scaler.update()
Warning: Nightly builds are on the bleeding edge and may contain bugs.
conda install pytorch torchvision torchaudio pytorch-cuda=12.6 -c pytorch -c nvidia Use code with caution. Compatibility between CUDA 12.6 and PyTorch
For LLM developers, is a critical component.
Calculator Online
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